Results 91 to 100 of about 15,287 (197)
Visual geo-localization using prior map of known environments has extensive applications in the fields such as self-driving, augmented reality and navigation. Currently, such prior maps are usually constructed by visual SLAM or SFM.
Zhiyuan Yang +13 more
doaj +1 more source
ABSTRACT This paper details the design and development of SensHB.Q, a force‐sensitive handlebar intended for caregivers driving electric‐powered wheelchairs, particularly those with omnidirectional mobility. The same interface can also be used in the future to operate other omnidirectional motorized systems, such as mobile robots, hospital beds, and ...
Luigi Tagliavini, Giuseppe Quaglia
wiley +1 more source
LO-Net: Deep Real-time Lidar Odometry
We present a novel deep convolutional network pipeline, LO-Net, for real-time lidar odometry estimation. Unlike most existing lidar odometry (LO) estimations that go through individually designed feature selection, feature matching, and pose estimation ...
Chen, Shaoyang +6 more
core +1 more source
ABSTRACT Personal autonomous vehicles can sense their surrounding environment, plan their route, and drive with little or no involvement of human drivers. Despite the latest technological advancements and the hopeful announcements made by leading entrepreneurs, to date no personal vehicle is approved for road circulation in a “fully” or “semi ...
Xingshuai Dong +13 more
wiley +1 more source
IaNDT-SLAM: intensity-augmented NDT for robust LiDAR-inertial SLAM in unstructured environments
Light detection and ranging (LiDAR) simultaneous localization and mapping (SLAM) has proven effective for robust perception in challenging environments.
Xin Yang +6 more
doaj +1 more source
The method of simultaneous localization and mapping (SLAM) using a light detection and ranging (LiDAR) sensor is commonly adopted for robot navigation. However, consumer robots are price sensitive and often have to use low-cost sensors.
Guolai Jiang +5 more
doaj +1 more source
: In this work, Voxel‐SLAM (simultaneous localization and mapping) is introduced: a complete, accurate, and versatile LiDAR (light detection and ranging) ‐inertial SLAM system consisting of five modules: initialization, odometry, local mapping (LM), loop closure (LC), and global mapping (GM), all employing the same map representation, an adaptive voxel
Zheng Liu +9 more
wiley +1 more source
3D As‐Built Environments in Extended Reality Applications: A Systematic Review
This systematic review identifies BIM and game engines as the primary tools for integrating 3D as‐built environments into XR. While multi‐sensor fusion and multimodal interaction enhance immersion, persistent challenges like manual modeling and bandwidth limitations continue to hinder full ecosystem maturation.
Jesús Balado +4 more
wiley +1 more source
Current substation inspection robots mainly use Lidar as a sensor for localization and map building. However, laser SLAM has the problem of localization error in scenes with similar and missing environmental structural features, and environmental maps ...
Yicen Liu, Songhai Fan
doaj +1 more source
CURL-SLAM: Continuous and Compact LiDAR Mapping
This paper studies 3D LiDAR mapping with a focus on developing an updatable and localizable map representation that enables continuity, compactness and consistency in 3D maps. Traditional LiDAR Simultaneous Localization and Mapping (SLAM) systems often rely on 3D point cloud maps, which typically require extensive storage to preserve structural details
Kaicheng Zhang +4 more
openaire +2 more sources

